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      <h1 class="index-header">
        
        <a href="/walker_sue/2021/01/25/week3-weekday/">时间序列分析（三） 周期因子</a>
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          机器学习-BI


Week_03
时间序列规则--周期因子


时间序列预测在对时间序列问题进行建模预测之前，通常可以通过一些简单的规则对结果进行提前的预测，可以作为baseline，供之后的模型进行参考。很多数据分析的比赛，都可以基于对于背景的理解和数据分析获得有用的规则，通过”if A then B”等方式设计出很好的基准方案。

一般我们可以采取一些简单的统计量作为特征：

中位数：较为稳
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              2021-01-25
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              <a href="/walker_sue/tags/%E6%97%B6%E9%97%B4%E5%BA%8F%E5%88%97%E5%88%86%E6%9E%90/">时间序列分析</a>
            
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        <a href="/walker_sue/2021/01/19/BI-week2-Prophet/">时间序列分析（二）Prophet</a>
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          机器学习-BI


Week_02
时间序列实战




Outline

prophet安装
Prophet预测模型
Prophet预测模型的优化


一、时间预测算法prophet1 Windows环境下fbprophet包的安装1.1 电脑安装anaconda环境，创建一个python3.7的conda环境。通过以下命令： 
conda create -n py37 python=3.7
1
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              2021-01-19
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              <a href="/walker_sue/tags/%E6%97%B6%E9%97%B4%E5%BA%8F%E5%88%97%E5%88%86%E6%9E%90/">时间序列分析</a>
            
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        <a href="/walker_sue/2020/12/30/BI-week1-ARIMA/">时间序列分析（一）</a>
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        <a href="/walker_sue/2020/12/30/BI-week1-ARIMA/">
          
          
            
          
          机器学习-BI


Week_01
时间序列分析




Outline

时间序列的概念
时间序列的基本特性及其分解
时间序列分析的常用统计模型：AR、MA、ARMA、ARIMA
LSTM进行时间序列预测
PM2.5数据基于时序预测的实现
时序数据库



一、时间序列概念时间序列定义: 按时间顺序排列的随机变量序列。          观测样本: 时间序列各随机变量的观测样本。一定是有限多个。
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              2020-12-30
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              <a href="/walker_sue/tags/%E6%97%B6%E9%97%B4%E5%BA%8F%E5%88%97%E5%88%86%E6%9E%90/">时间序列分析</a>
            
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        <a href="/walker_sue/2020/11/05/NLP_week1/">NLP阅读理解Week1 学习笔记</a>
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        <a href="/walker_sue/2020/11/05/NLP_week1/">
          
          
            
          
          机器阅读理解


Week 01
课程介绍与基础概念解析


课程结构
课程介绍与基础概率解析
常见的机器阅读理解模型（一）
常见的机器阅读理解模型（二）
BERT与机器阅读理解
其他预训练语言模型与阅读理解
基于预训练模型与其他策略扩展的阅读理解模型
模型集成、优化及部署
课程总结与NLP面试指导

NLP简介定义介绍自然语言处理，英文Natural Language Processing，简写
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              2020-11-05
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